The hardest parts of data science
Defining feasible problems and coming up with reasonable ways of measuring solutions is harder than building accurate models or obtaining clean data.
Kaggle
Learning to rank for personalised search (Yandex Search Personalisation – Kaggle Competition Summary – Part 2)
My team’s solution to the Yandex Search Personalisation competition (finished 9th out of 194 teams).
Is thinking like a search engine possible? (Yandex search personalisation – Kaggle competition summary – part 1)
Insights on search personalisation and SEO from participating in a Kaggle competition (finished 9th out of 194 teams).
Fitting noise: Forecasting the sale price of bulldozers (Kaggle competition summary)
Summary of a Kaggle competition to forecast bulldozer sale price, where I finished 9th out of 476 teams.
What is data science?
Data science has been a hot term in the past few years. Still, there isn’t a single definition of the field. This post discusses my favourite definition.
Greek Media Monitoring Kaggle competition: My approach
Summary of my approach to the Greek Media Monitoring Kaggle competition, where I finished 6th out of 120 teams.
How to (almost) win Kaggle competitions
Summary of a talk I gave at the Data Science Sydney meetup with ten tips on almost-winning Kaggle competitions.
Kaggle competition tips and summaries
Pointers to all my Kaggle advice posts and competition summaries.
Kaggle beginner tips
First post! An email I sent to members of the Data Science Sydney Meetup with tips on how to get started with Kaggle competitions.